Systematic review of time lag between antibiotic use and rise of resistant pathogens among hospitalized adults in Europe

Abstract Background Antimicrobial resistance (AMR) causes substantial health and economic burden to individuals, healthcare systems and societies globally. Understanding the temporal relationship between antibiotic consumption and antibiotic resistance in hospitalized patients can better inform antibiotic stewardship activities and the time frame for their evaluation. Objectives This systematic review examined the temporal relationship between antibiotic use and development of antibiotic resistance for 42 pre-defined antibiotic and pathogen combinations in hospitalized adults in Europe. Methods Searches in MEDLINE, Embase, Cochrane Library and NIHR Centre for Reviews and Dissemination were undertaken from 2000 to August 2021. Pathogens of interest were Escherichia coli, Klebsiella pneumoniae, Streptococcus pneumoniae, Staphylococcus aureus, Enterococcus faecium, CoNS, Pseudomonas aeruginosa and Acinetobacter baumannii complex. Results Twenty-eight ecological studies and one individual-level study were included. Ecological studies were predominantly retrospective in design (19 studies) and of reasonable (20 studies) to high (8 studies) methodological quality. Of the eight pathogens of interest, no relevant data were identified for S. pneumoniae and CoNS. Across all pathogens, the time-lag data from the 28 ecological studies showed a similar pattern, with the majority of studies reporting lags ranging from 0 to 6 months. Conclusions Development of antibiotic resistance for the investigated antibiotic/pathogen combinations tends to occur over 0 to 6 months following exposure within European hospitals. This information could inform planning of antibiotic stewardship activities in hospital settings.


Introduction
Antimicrobial resistance (AMR) is associated with substantial health and economic burden to individuals and healthcare systems. 1,2 The WHO 3,4 promotes antibiotic stewardship (ABS) programmes and activities in an effort to optimize the use of antibiotics and slow down the dramatic increasing trend in antibiotic resistance. Those efforts are supported by European institutions and initiatives, e.g. European Center for Disease Prevention and Control (ECDC), and addressed in national action plans to combat antibiotic resistance. 5 For local ABS activities, robust surveillance data are needed about antibiotic use and antibiotic resistance in clinical settings as well as an integrated analysis of data from both, often independently implemented, surveillance systems. A tool for the integrated analysis of antibiotic consumption and resistance data was developed for hospitals in Germany in 2019 to support local ABS activities and programmes. 6 One challenge in interpreting data in an integrative approach and mathematical modelling of AMR is the temporal relationship between antibiotic consumption (i.e. drug pressure) and the development of AMR. Previous reviews [7][8][9][10] have assessed the temporal relationship between antibiotic consumption and development of resistance in ambulatory and primary care settings. Generally, the reviews 7-9 found evidence for an association between antibiotic consumption and the development of bacterial resistance, while findings on evidence for associations as well as time to emergence of resistance were not consistent for all antibiotics or bacteria. This may be explained by differences in review methodologies and scopes. Bell and colleagues 7 included 243 studies (case-control, cross-sectional, ecological and experimental studies) across all antibiotics and bacteria. 7 The time between consumption and resistance was 6 months or less in 53%, more than 6 months in 23%, and unclear in the remainder of the included studies. 7 Costelloe et al. 8 analysed 24 observational or experimental studies. Ecological studies that focused predominantly on the emergence of antibiotic resistance associated with urinary, respiratory or skin infections were excluded from this review. 8 The review found that AMR developed shortly after antibiotic exposure (i.e. within 1 month) but gradually waned over time (up to 3 to 12 months). 8 Bakhit and others, 9 on the other hand, included 25 individual-level studies of varied study designs involving 1461 adults and 16 353 children and noted that resistance increased immediately after treatment and generally persisted for 1 to 3 months.
This current review was undertaken to provide better understanding of the body of evidence on the temporal relationship between antibiotic consumption and emergence of resistance in hospitalized patients. Temporal relationship is likely to vary between different countries with differing healthcare systems; one important consideration was the context (e.g. relating to treatment guidelines; infection prevention and control protocols; ABS practices, standards of AMR measurement; care setting and baseline resistance) of available evidence. For this reason, this review focuses on hospitals within Europe.

Methods
The review examined the temporal relationship between antibiotic consumption and the development of antibiotic resistance. The review protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) on 1 September 2021 and was last updated on 11 January 2022 (registration number CRD42021274957).

Literature searches
Searches in MEDLINE, Embase, the Cochrane Library and archives of the NIHR Centre for Reviews and Dissemination (CRD) were undertaken in August 2021. The MEDLINE search strategy (File S1, available as Supplementary data at JAC-AMR Online) was adapted for use in other bibliographic databases. Search terms related to antibiotic resistance and antibiotic consumption or exposure. The search was conducted with and without additional terms for the hospital setting. All records from searches using hospital terms were checked in full. However, records from the broader search without hospital terms were considered as an extra data source and were screened using targeted keywords such as time-series, ARIMA, temporal, lag, cross-correlation, delay and dynamic transfer function. Based on previous reviews, 7-10 a publication year limit from 2000 onwards was applied to reflect current trends of antibiotic resistance.
Supplementary searches using targeted keywords, as referred to earlier, were conducted in websites of international and national organizations including the ECDC, the Robert Koch Institute (RKI), the Surveillance Network France, Instituto de Salud Carlos III, WHO and the US CDC. Reference lists of included studies and relevant reviews were also examined to identify additional publications.

Inclusion and exclusion criteria
Eligible study types were ecological studies and individual-level studies reporting on the temporal relationship between antibiotic use and subsequent emergence of antibiotic resistance for specific antibiotic and pathogen (drug/bug) combinations (See Files S2 and S3). Ecological studies generally reported the time lag that provided the best-fit correlation between time series for antibiotic consumption and resistance. Whereas individual studies reported time-lag data, which could consist of either ORs for resistance in patients with/without prior antibiotic exposure at different timepoints or the number of days to resistance development in individuals receiving antibiotics.
Eight pathogens were considered, based on the WHO priority pathogens list for research and development: 11 Escherichia coli, Klebsiella pneumoniae, Streptococcus pneumoniae, Staphylococcus aureus, Enterococcus faecium, Coagulase-negative Staphylococci (CoNS), Pseudomonas aeruginosa and Acinetobacter baumannii complex, with the potential to broaden to other species within the same genus in the event of limited data on a specific pathogen. The population of interest was hospitalized adults (or studies in mixed age groups), colonized or infected with pathogens of interest. Studies conducted within Europe, considered as the EU, European Economic Area (EEA) and the UK, were eligible for inclusion. Where limited data were identified for any pathogen, the potential to broaden the selection criteria to high-or middle-income countries outside the EU/EEA was considered. Studies published in English, German, French or Spanish from 2000 to August 2021 were included.
Exclusion criteria were as follows: studies with a publication date preceding 2000, coinfection with multiple pathogens, studies specific to children, the use of combination preparations of antibiotics, and studies conducted in low-income countries.

Study selection
A two-staged selection of studies was conducted using pre-specified criteria. Two reviewers (E.P. or K.C.) checked titles and abstracts of retrieved records. One reviewer checked titles and abstracts of retrieved records. A second reviewer examined a 10% sample, early in the selection process. The two reviewers compared and discussed title and abstract decisions for the initial screening in order to improve consistency of subsequent study selection. The level of agreement between two reviewers during the initial selection process resulted in a kappa statistic of 0.84, indicating very good agreement. Disagreements were resolved by consensus following re-examination of the review protocol and feedback from the wider review team. The two reviewers discussed their understanding of the eligibility criteria at this stage to improve agreement in the next stages of the selection process. Subsequently, full-text articles of selected abstracts were then checked for eligibility. Any disagreements were resolved by discussion or referral to a third researcher when needed.

Data extraction and quality assessment
Data were extracted into a pre-piloted Microsoft Excel ® form. Abstracted data included study characteristics, antibiotic susceptibility testing methods, antibiotic use and temporal relationship between antibiotic use and emergence of resistance. Data were checked by a second reviewer.
In the absence of an appropriate relevant quality assessment tool, bespoke criteria were applied to assess the methodological quality and relevance of included studies. Selected criteria were informed by the recommendations of the Quality Assessment Tool for Quantitative Studies set out by the Effective Public Health Practice Project (https:// www.ephpp.ca/PDF/QADictionary_dec2009.pdf) and the quality appraisal approach reported by Costelloe and colleagues. 8 For ecological studies, assessment of included studies focused on: (1) generalizability of findings to hospitalized adults within Europe; (2) reliability of quantifying antibiotic use; (3) reliability of reporting antibiotic resistance; (4) appropriateness of Systematic review study design to estimate a temporal relationship (e.g. time lag) between antibiotic use and emergence of resistance; and (5) adjustment(s) for key confounders such as other antibiotic use and/or infection control measures. For studies with an individual-level study design, an additional item related to: (6) unbiased selection of a control group was assessed. Criteria were rated as 'yes', 'no' or 'unclear'. Studies with five or more 'yes' responses were considered high quality; three to four 'yes' responses were considered to be reasonable quality and those with less than three 'yes' responses were noted as low quality. Details of applied criteria are outlined in File S4.

Data synthesis
Data were summarized and presented in narrative and tabular summaries. Extensive clinical and methodological heterogeneity was noted in included ecological and individual-level studies. Time-lag outcomes reported in ecological studies were presented as discrete outcomes (e.g. lag of 1 month) or a range of outcomes, with limited or no information about uncertainty. For these reasons, meta-analysis was considered to be inappropriate.

Results
Overall, 28 ecological 12-39 and one case-control study 40 were eligible for inclusion ( Figure 1). The case-control study reported by Dualleh et al. 40 assessed the effect of antibiotic use (0 to 6 months, 6 to 12 months or 12 to 24 months prior to enrolment) on colonization with extended-spectrum β-lactamase (ESBL)-producing Enterobacterales. Prior use of fluoroquinolones during all three time periods was associated with incidence of ESBL-producing Enterobacterales, while prior use of penicillins or macrolides showed mixed results. 40 Details of the individual-level study 40 are presented separately in File S5 because of the differences in study designs and the available data on time-lag outcomes compared with the 28 ecological studies. Therefore, the synopsis here focuses on the ecological studies.

Study quality and relevance
Overall, all 28 ecological studies met most quality assessment items and were of reasonable (20 studies) to high quality (8 studies). A summary of methodological quality of ecological studies is presented in Table 2. Applied criteria are outlined in File S4.
Eight studies 13,24,28,29,34,36-38 scored 'yes' for all quality assessment items, whilst a further 12 studies 13,15,18,[21][22][23]26,[30][31][32][33]35 scored 'yes' for four out of five items and 8 studies 14,16,17,19,20,25,27,39 scored 'yes' for three out of five items. Therefore, 8 studies were of high quality while the other 20 studies were of reasonable quality according to the applied quality criteria. The item relating to the generalizability of the findings scored well in all 28 studies, since all studies were based in Europe, and measured antibiotic use and resistance in a hospital setting. The item that scored 'yes' the least frequently related to adjustments made in the analysis; however, 16 studies scored well. Analyses were not adjusted for other antibiotic use and infection control measures in four studies. 12,14,16,27 A further seven studies scored 'unclear' for this item. [16][17][18][19][20]31,39 The item relating to the methods used to assess resistance was often poorly reported, with 10 studies 14,19,[21][22][23]27,30,33,35,39 scoring 'unclear' for this item. This was usually because the laboratory methods used to ascertain susceptibility were not reported or the breakpoints or standards used to interpret susceptibility were not reported ( Table 2).

Outcomes of interest
Relevant outcome data were available for six of the eight pathogens of interest: E. coli, K. pneumoniae, S. aureus, E. faecium, P. aeruginosa and A. baumannii. No relevant data were identified for S. pneumoniae and CoNS, either for Europe or for other high-or middle-income countries. For some pathogens only limited data could be identified. Therefore, broadening the eligibility criteria led to the inclusion of a study conducted in Serbia 31 and studies relating to broader genera of pathogens, such as Klebsiella spp., Vancomycin-resistent Enterococci (VRE), Acinetobacter spp. and ESBL producers including Enterobacterales.
To assess the strength of the association between antibiotic use and antibiotic resistance, most ecological studies conducted time-series analyses for both antibiotic use and resistance, then used correlation or regression analyses to assess the strength of the relationship. The time lag that gave the strongest association was then reported. The majority of analyses were multivariate with adjustments for prior resistance levels; 14,15,21-23, 26,27,30,33 community antibiotic use 13,12,32,34,35 and simultaneous in-hospital antibiotic use. 21,[23][24][25][26]28,30,[32][33][34][35][36][37] Analyses were also adjusted for: infection control procedures (not specified); 13 use of alcohol-based hand rub; 13,21,22 prior 30,32 or current frequency of admitted or screened patients with resistant pathogens; 21,22,24 bed occupancy 24 and length of hospital stay. 24 Time-lag data were generally reported where a statistically significant association existed between antibiotic use and resistance; however, a few studies reported time-lag data for non-significant associations, which were included in a best-fit multivariate model. Tables 3-6 summarize the findings reported in ecological studies; details are presented in File S6.

Klebsiella spp.
Four studies 19,31,33,39 assessed time-lag data in Klebsiella spp. (Tables 3 and 4). Two studies 31,39 focused on K. pneumoniae only, while one study 33 included K. pneumoniae and Klebsiella  oxytoca, and one study 19 included multiple Klebsiella species. Across all studies, the time lag ranged from 1 to 3 months in one study 19 and 1 to 6 months in another, 33 while in the two studies that aggregated data yearly, the time lag was 0 to 1 years. 31,39 Carbapenem use was associated with carbapenem resistance (lag, 1 to 6 months 19,33 or within the same year 31 or the previous year 39 ), with fluoroquinolone resistance (lag, 2 to 3 months 19 ) and with polymyxin resistance (within the same year 31 ). Cephalosporin use was associated with cephalosporin resistance (lag, 1 to 6 months 33 ) and with carbapenem and polymyxin resistance (in the same year 31 ).
Fluoroquinolone use was associated with fluoroquinolone resistance (lag, 2 to 3 months 19 ) and with carbapenem and polymyxin resistance (in the following year 31 ). Penicillin + β-lactamase inhibitor use was associated with polymyxin resistance (in the following year 31 ). Polymyxin use was associated with carbapenem resistance (in the same and the following year 31 ) and with polymyxin resistance (in the same year 31 ).

Acinetobacter spp.
Two studies 26,33 focused on A. baumannii while one study 31 included multiple Acinetobacter spp. (Tables 3 and 6). Carbapenem use was associated with carbapenem resistance (lag, 1 to 4 months 26,33 ) while fluoroquinolone use was associated with carbapenem resistance (lag, 1 month, 26 or in the subsequent year in a study 31 that aggregated data yearly).

ESBL-producing bacteria
Three ecological studies 12,21,36 assessed time-lag data for combined groups of ESBL-producing bacteria (Tables 3 and 6). Studies were included in the review as they included some pathogens relevant to the inclusion criteria. One study 36 included E. coli, K. pneumoniae and E. cloacae; one study 21 included E. coli, E. cloacae, Klebsiella, Acinetobacter spp. and Citrobacter spp.; and the remaining study 12 did not specify the pathogen types. Across all studies, the time lag was 1 to 2 months in one study, 12 1 to 3 months in another study 21 and 1 to 5 months in a third study. 36 Penicillin use (with or without β-lactamase inhibitors) was associated with ESBL production (lag, 1 to 5 months 36 ). The use of 1 + 2G cephalosporins and 3 + 4G cephalosporins were associated with ESBL production (lag, 1 month 36 and 3 to 5 months, 21,36 respectively). ESBL production was also associated with carbapenem use (lag, 2 months 36 ) and fluoroquinolone use (lag, 1 to 3 months 12,21,36 ).

Discussion
This review summarized evidence relating to the temporal relationship between antibiotic consumption and resistance for specific drug/bug combinations in eight pathogens (E. coli, K. pneumoniae, S. pneumoniae, S. aureus, E. faecium, CoNS, P. aeruginosa and A. baumannii complex) in hospitalized patients in the EU, the EEA and the UK. Broadening of the eligibility criteria to include studies in high-and middle-income countries was applied due to limited data; however, no relevant studies were identified for S. pneumoniae or CoNS. The time-lag data were mainly reported where there was a significant association between antibiotic exposure and antibiotic resistance. It is unclear whether time-lag data would be meaningful where there is no significant association. Therefore, the likelihood of publication bias was not considered in this review.
The most investigated pathogen was P. aeruginosa (10 studies) followed by S. aureus/MRSA (8 studies) and E. coli (5 studies).   Across all pathogens, the time-lag data from the 28 ecological studies showed a similar pattern, with the majority of studies reporting time lags ranging from 0 to 6 months. In E. coli (5 studies), the time lag ranged from 0 to 6 months across four studies 18,26,28,34 and 1 to 12 months in one study. 33 In Klebsiella spp. (four studies), the time lag ranged from 1 to 3 months in one study 19 and 1 to 6 months in another, 33 while in two studies that aggregated data yearly, the time lag was 0 to 1 years. 31,39 In S. aureus (8 studies), the time lag ranged from 0 to 7 months across the eight studies. 13,22,24,26,29,30,35,38 In enterococci (two studies, both of VRE), the time lag was 1 month in one study 32 and 2 to 6 months in the other. 23 For P. aeruginosa (10 studies), the time lag ranged from 0 to 2 months across six studies 14,17,[25][26][27]33 and from 0 to 6 months across two further studies, 16,20 while in two additional studies that aggregated data quarterly, the time lag was 0 to 1 quarter in one 15 and 0 to 2 quarters in the other. 37 In Acinetobacter spp. (three studies), the time lag ranged from 1 to 4 months in two studies 26,33 and was 1 year in a further study that aggregated data yearly. 31 In ESBL-producing pathogens (three studies), the time lag was 1 to 2 months in one study, 12 1 to 3 months in another study 21 and 1 to 5 months in a third study. 36 Ecological studies reported the time lag for the model with the best fit for assessing the association between antibiotic consumption and resistance and collected data monthly or quarterly. While most studies report time lags to appearance of antibiotic resistance of 0 to 6 months, one study reported time lags of 0 to 12 months. 33 The range of 0 to 12 months includes the early appearance of resistance in the first 6 months after exposure to antibiotics and is therefore consistent with the findings of the majority of studies included in this review. We consider the reported time lags of up to 12 months in this study to reflect the length of persistence of antibiotic resistance once acquired. Two further studies 31,39 report time lags of 12 months, but aggregated data yearly, which does not allow for assessing early appearance of resistance but supports the finding that antibiotic resistance (once acquired) can persist in the hospital setting for several months.
The findings of this review overall correspond to findings of two reviews conducted in the ambulatory setting. Costelloe  21 ) and ESBL-producing bacteria, not specified (one study 12 ). et al. 8 reviewed studies at the individual level and assessed the strength of associations of antibiotic consumption and resistance across different time periods. 8 For E. coli from urinary tract infections, the strongest association was found for a time lag of 0 to 1 months, with a constant decrease of the strength of association with increasing time lags (0 to 3, 0 to 6 and 0 to 12 months, respectively). The analysis of pathogens of respiratory tract infections, including S. pneumoniae, in the reviews of Costelloe et al. 8 and Bakhit et al. 9 revealed an association of exposure to antibiotics and emergence of resistance within the first 3 months after exposure to various antibiotics. For S. pneumoniae, a pathogen causing community-acquired lower respiratory tract infections that usually do not require inpatient care, no relevant studies were identified in this review. It is worth noting that individuallevel studies may find shorter time lags than ecological studies, which take into account spread of resistance within a population or setting. Overall, the current findings did not demonstrate substantial differences between classes of antibiotics or pathogens in terms of the outcome of interest.
Evidence relating to time lags for cross-resistance do not differ from those of concordant antibiotic classes. Overall, the review found that carbapenems and fluoroquinolones were most commonly associated with cross-resistance in a number of pathogens. Available literature supports the occurrence of cross-resistance following the use of carbapenems and fluoroquinolones in hospital settings. 41,42 The review also found that cross resistance was reported most commonly for P. aeruginosa isolates. This may be explained by the volume of available relevant evidence. On the other hand, P. aeruginosa is known to be a major cause of hospital-acquired infections, which also possesses an inherent characteristic for the emergence of resistant strains, both for concordant and discordant antibiotic classes. Both characteristics may influence a propensity for crossresistance due to antibiotic selection pressure. Overall, time lags for discordant antibiotic classes of antibiotic exposure and resistance did not appear to differ from those of concordant antibiotic classes, with both sets of time lags ranging from 0 to 6 months. P. aeruginosa, S. aureus and appearance of MRSA are the most investigated pathogens within the studies included in this review. While resistance to fluoroquinolones and lincosamides within studies of S. aureus appears with a time lag of 0 to 5 months (time lag in two studies: 0 months in one study; 24 0 to 5 months in the other study 38 ), resistance to methicillin/oxacillin (appearance of MRSA) tends to occur with a slightly greater time lag (range between 1 and 7 months in seven studies). This is surprising against the background that MRSA has the potential to be identified in colonized patients through screening measures and therefore should potentially be identified at an early stage. Hygiene measures such as isolation of patients at risk for MRSA or decolonization might explain this slightly later appearance of MRSA compared with resistance of fluoroquinolones and lincosamides in S. aureus. Overall, this difference in time lags should not be overinterpreted, since the different time lags derive from different studies applying different methodologies. Only the study by Lawes et al. 24 investigated both resistance to fluoroquinolones in S. aureus and incidence of MRSA, with results supporting the trend described.

Strengths and limitations
This review presents the most recent findings on the temporal relationship between antibiotic consumption and resistance for specific drug/bug combinations in European hospitals. Studies published since 2000 were identified to reflect data that are more relevant to current antibiotics, trends in resistance and settings. The search strategy led to the identification of an acceptable evidence base. Included studies were of reasonable to high methodological quality, although retrospective study designs were common. Most used standardized measures for data on antibiotic use and microbiological information and scored well on analytical methods.
There are a few limitations of this review. Firstly, it was not possible to assess the impact of potential confounders on timelag outcomes, especially for studies that did not clearly present this information. For example, the review included studies conducted in diverse hospital departments where patients may have a range of comorbidities, and patient management including infection control and ABS measures adds to the complexity of different exposures and might have had an additional effect on resistance. The impact of these factors on selection pressure for resistance was not possible to elucidate, due to reported analyses. Secondly, due to study design and available data in the hospital setting, development of resistance was mostly analysed based on aggregated ecological data. Additionally, the potential effect of transmission could not be assessed systematically. The wider use of electronic health records may overcome some of these limitations and result in patient-based data collection and analyses for antibiotic use and subsequent resistance in the hospital setting.
Thirdly, the inclusion of studies reporting on pathogen genus instead of defined species may limit the generalizability of results. However, in the absence of data per species, this information could be a reasonable proxy for decision-making. Furthermore, the effect of 1G and 2G cephalosporins and different active substances of fluoroquinolones could not be assessed separately because included studies presented data of these antibiotics grouped as presented in this review. Fourthly, the available data did not permit analysis of the dose-effect and treatment duration on time-lag outcomes, nor in detail the time to resistance decay. Finally, study selection was completed by two reviewers with a robust checking of the study selection process. There is a risk of having missed relevant studies, which overall we consider to be minimal.

Conclusions
The available evidence from ecological studies suggests that the development of antibiotic resistance for specific drug/bug combinations within a hospital population mainly occurs between 0 to 6 months after use of related antibiotics within European hospitals. Knowledge on the time lag for emergence of antibiotic resistance after antibiotic exposure for a set of comprehensive drug/bug combinations could help define time periods for monitoring and evaluation of ABS interventions and inform tools modelling the association of antibiotic exposure and resistance to support ABS activities in hospitals. Evidence on the time lag between reduction of antibiotic use and subsequent decline in Systematic review resistant pathogens as a result of ABS is not reviewed yet and should be part of further reviews.